Electronic commerce systems traditionally comprise a marketplace of hundreds to thousands of items available for purchase. Navigating the vast number of items in an electronic commerce system traditionally requires a user to conduct various searches using a search engine or requires a user to navigate an extensive item taxonomy to dial down to an item page describing an item. The item page may show one or more images of the item and may provide a detailed description. Yet, it remains difficult for the user to perceive how an item may look in a particular setting. For example, if the user navigates to the item page for a sofa, it is difficult for the user to visualize how the sofa may look in a living room, a dining room, or a similar setting. Moreover, the user may not have knowledge about decorating trends, style habits, color pallets, etc.
Computer vision relates to analyzing, interpreting, understanding, and deriving information from digital images obtained via digital cameras or similar image capturing devices. Such information may be used in automated color detection, depth perception, and object recognition in computing environments. Information may be derived in computer vision by analyzing or comparing each pixel in the digital image to determined thresholds such that colors may be detected and objects may be recognized.